1 Détermination des motifs fixés par Shavenbaby dans les S2 et les embryons

1.1 Stringent

## $p.value
##      Svb_S2 Svb_embryo. svbF7 pval
## [1,]      0           1     1  NaN
## [2,]      1           0     1  NaN
## [3,]      1           1     0  NaN
## 
## $vennCounts
##      Svb_S2 Svb_embryo. svbF7 Counts count.B1.peaks count.SvbACT.peaks_embryo
## [1,]      0           0     0 -13114              0                         0
## [2,]      0           0     1   1108              0                         0
## [3,]      0           1     0   6374              0                      6374
## [4,]      0           1     1    581              0                       823
## [5,]      1           0     0   3645           3645                         0
## [6,]      1           0     1    219            300                         0
## [7,]      1           1     0    964           1004                      1003
## [8,]      1           1     1    323            563                       506
##      count.svbF7_cons_gr
## [1,]                   0
## [2,]                1108
## [3,]                   0
## [4,]                 630
## [5,]                   0
## [6,]                 239
## [7,]                   0
## [8,]                 377
## attr(,"class")
## [1] "VennCounts"
svbF7_motifs_unbound_svb = as.data.frame(motif_svb_Bind_overlap_cell$peaklist$svbF7_cons_gr)

svbF7_motifs_bound_svb = as.data.frame(motif_svb_Bind_overlap_cell$peaklist$`B1.peaks///SvbACT.peaks_embryo///svbF7_cons_gr`)

svbF7_motifs_S2 = as.data.frame(motif_svb_Bind_overlap_cell$peaklist$`B1.peaks///svbF7_cons_gr`)

svbF7_motifs_embryo = as.data.frame(motif_svb_Bind_overlap_cell$peaklist$`SvbACT.peaks_embryo///svbF7_cons_gr`)

2 Comparaison avec les histones

2.1 Comparaison sur les motifs fixés dans les S2 et les embryons

2.1.1 H3K27ac

in H3K27ac absent H3K27ac
in svbF7 unbound 193 745
absent svbF7 unbound 4955 7979
in H3K27ac absent H3K27ac
in svbF7 bound 267 28
absent svbF7 bound 4886 8254
presence = c(267,4886)
absence = c(28,8254)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
pvalue_fixe = phyper(193 - 1, 938, 13872 - 938, 5148)
pvalue_nonfixe = phyper(267 - 1, 295, 13435 - 295, 5153)
contingence_H3K27ac_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K27ac_fixe)

presence = c(193,4955)
absence = c(745,7979)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K27ac_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K27ac_nonfixe)

La pvalue du test de fisher pour les motifs fixé est de 2.938327510^{-80} Celle du test de fisher pour les motifs non fixé est de 1.590738210^{-29}`

La pvalue du test de hypergéométrique pour les motifs fixé est de 3.611226810^{-30} Celle du test de hypergéométrique pour les motifs non fixé est de 1

total_svbF7_unbound_H3K27ac = 193 + 745
total_svbF7_bound_H3K27ac = 267 + 28

percent_svbf7_H3K27ac_unbound = round(100 * 193 / total_svbF7_unbound_H3K27ac, 2 ) 
percent_svbf7_unbound_without_H3K27ac = round(100 * 745 / total_svbF7_unbound_H3K27ac, 2 ) 

percent_svbf7_H3K27ac_bound = round(100 * 267 / total_svbF7_bound_H3K27ac, 2 ) 
percent_svbf7_bound_without_H3K27ac = round(100 * 28 / total_svbF7_bound_H3K27ac, 2 ) 


etat_svb = c("svbF7_bound","svb_unbound")
H3K27ac_absent = c(percent_svbf7_bound_without_H3K27ac,percent_svbf7_unbound_without_H3K27ac)

H3K27ac_present = c(percent_svbf7_H3K27ac_bound,percent_svbf7_H3K27ac_unbound)

data_H3K27ac = data.frame(etat_svb,H3K27ac_absent,H3K27ac_present)
datatable(data_H3K27ac,rownames = F,filter = "none",colnames = c("Regions without H3K27ac","Regions with H3K27ac" ))
fig1 = plot_ly(data_H3K27ac, x = ~etat_svb,y = ~H3K27ac_absent, type = "bar",name = "H3K27ac absent")
fig1 = fig1 %>% add_trace(y = ~H3K27ac_present, name = "H3K27ac present")
fig1 = fig1 %>% layout(yaxis = list(title = "percent"))
fig1 = fig1 %>% layout(title = "H3K27ac enrichment on svbF7 bound or not by Svb")
fig1
fig1 = plot_ly(data_H3K27ac, x = ~etat_svb,y = ~H3K27ac_absent, type = "bar",name = "H3K27ac absent")
fig1 = fig1 %>% add_trace(y = ~H3K27ac_present, name = "H3K27ac present")
fig1 = fig1 %>% layout(yaxis = list(title = "percent"))
fig1 = fig1 %>% layout(title = "H3K27ac enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig1

2.1.2 H3K27me3

in H3K27me3 absent H3K27me3
in svbF7 unbound 1241 0
absent svbF7 unbound 12191 4566
in H3K27me3 absent H3K27ac
in svbF7 bound 190 105
absent svbF7 bound 13248 3723
pvalue_fixe = phyper(190 - 1, 295, 17266 - 295, 13438)
pvalue_nonfixe = phyper(1241 - 1, 938, 17998 - 938, 13432)

presence = c(190,13248)
absence = c(105,3723)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K27me3_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K27me3_fixe)

presence = c(1241,12191)
absence = c(0,4566)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K27me3_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K27me3_nonfixe)

La pvalue du test de fisher pour les motifs fixé est de 1.255137810^{-7} Celle du test de fisher pour les motifs non fixé est de 8.667719310^{-165}`

La pvalue du test de hypergéométrique pour les motifs fixé est de 3.998180410^{-8} Celle du test de hypergéométrique pour les motifs non fixé est de 1

total_svbF7_unbound_H3K27me3 = 1241 + 0
total_svbF7_bound_H3K27me3 = 190 + 105

percent_svbf7_H3K27me3_unbound = round(100 * 1241 / total_svbF7_unbound_H3K27me3, 2 ) 
percent_svbf7_unbound_without_H3K27me3 = round(100 * 0 / total_svbF7_unbound_H3K27me3, 2 ) 

percent_svbf7_H3K27me3_bound = round(100 * 190 / total_svbF7_bound_H3K27me3, 2 ) 
percent_svbf7_bound_without_H3K27me3 = round(100 * 105 / total_svbF7_bound_H3K27me3, 2 ) 


etat_svb = c("svbF7_bound","svbF7_unbound")
H3K27me3_absent = c(percent_svbf7_bound_without_H3K27me3,percent_svbf7_unbound_without_H3K27me3)

H3K27me3_present = c(percent_svbf7_H3K27me3_bound,percent_svbf7_H3K27me3_unbound)

data_H3K27me3 = data.frame(etat_svb,H3K27me3_absent,H3K27me3_present)
datatable(data_H3K27me3,rownames = F,filter = "none",colnames = c("Regions without H3K27me3","Regions with H3K27me3" ))
fig2 = plot_ly(data_H3K27me3, x = ~etat_svb,y = ~H3K27me3_absent, type = "bar",name = "H3K27me3 absent")
fig2 = fig2 %>% add_trace(y = ~H3K27me3_present, name = "H3K27me3 present")
fig2 = fig2 %>% layout(yaxis = list(title = "percent"))
fig2 = fig2 %>% layout(title = "H3K27me3 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig2

2.1.3 H3K4me1

in H3K4me1 absent H3K4me1
in svbF7 unbound 324 614
absent svbF7 unbound 8441 6309
in H3K4me1 absent H3K4me1
in svbF7 bound 392 0
absent svbF7 bound 8380 6355
pvalue_fixe = phyper(392 - 1, 295, 15127 - 295, 8772)
pvalue_nonfixe = phyper(324 - 1, 938, 15688 - 938, 8765)

presence = c(392,8380)
absence = c(0,6355)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K4me1_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K4me1_fixe)

presence = c(324,8441)
absence = c(614,6309)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K4me1_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K4me1_nonfixe)

La pvalue du test de hypergéométrique pour les motifs fixé est de 1 Celle du test de hypergéométrique pour les motifs non fixé est de 2.462952910^{-42}

La pvalue du test de fisher pour les motifs fixé est de 5.299276610^{-95} Celle du test de fisher pour les motifs non fixé est de 1.095848110^{-41}`

total_svbF7_unbound = 324 + 614
total_svbF7_bound = 392 + 0 

percent_svbf7_H3K4me1_unbound = round(100 * 324 / total_svbF7_unbound, 2 ) 
percent_svbf7_unbound_without_H3K4me1 = round(100 * 614 / total_svbF7_unbound, 2 ) 

percent_svbf7_H3K4me1_bound = round(100 * 392 / total_svbF7_bound, 2 ) 
percent_svbf7_bound_without_H3K4me1 = round(100 * 0 / total_svbF7_bound, 2 ) 



etat_svb = c("svbF7_bound","svbF7_unbound")
H3K4me1_absent = c(percent_svbf7_bound_without_H3K4me1,percent_svbf7_unbound_without_H3K4me1)

H3K4me1_present = c(percent_svbf7_H3K4me1_bound,percent_svbf7_H3K4me1_unbound)

data_H3K4me1 = data.frame(etat_svb,H3K4me1_absent,H3K4me1_present)
datatable(data_H3K4me1,rownames = F,filter = "none", colnames = c("Regions without H3K4me1","Regions with H3K4me1" ))
fig3 = plot_ly(data_H3K4me1, x = ~etat_svb,y = ~H3K4me1_absent, type = "bar",name = "H3K4me1 absent")
fig3 = fig3 %>% add_trace(y = ~H3K4me1_present, name = "H3K4me1 present")
fig3 = fig3 %>% layout(yaxis = list(title = "percent"))
fig3 = fig3 %>% layout(title = "H3K4me1 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig3

2.1.4 H3K4me3

in H3K4me3 absent H3K4me3
in svbF7 unbound 92 846
absent svbF7 unbound 4715 11329
in H3K4me3 absent H3K4me3
in svbF7 bound 222 73
absent svbF7 bound 4586 11447
pvalue_fixe = phyper(222 - 1, 295, 16328 - 295, 4808)
pvalue_nonfixe = phyper(92 - 1, 938, 16982 - 938, 4807)
presence = c(222,4586)
absence = c(73,11447)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K4me3_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K4me3_fixe)

presence = c(92,4715)
absence = c(846,11329)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K4me3_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K4me3_nonfixe)

La pvalue du test de hypergéométrique pour les motifs fixé est de 1 Celle du test de hypergéométrique pour les motifs non fixé est de 1.633496410^{-46}

La pvalue du test de fisher pour les motifs fixé est de 2.255675910^{-60} Celle du test de fisher pour les motifs non fixé est de 1.080796610^{-45}`

total_svbF7_unbound_H3K4me3 = 92 + 846
total_svbF7_bound_H3K4me3 = 222 + 73

percent_svbf7_H3K4me3_unbound = round(100 * 92 / total_svbF7_unbound_H3K4me3, 2 ) 
percent_svbf7_unbound_without_H3K4me3 = round(100 * 846 / total_svbF7_unbound_H3K4me3, 2 ) 

percent_svbf7_H3K4me3_bound = round(100 * 222 / total_svbF7_bound_H3K4me3, 2 ) 
percent_svbf7_bound_without_H3K4me3 = round(100 * 73 / total_svbF7_bound_H3K4me3, 2 ) 



etat_svb = c("svbF7_bound","svbF7_unbound")
H3K4me3_absent = c(percent_svbf7_bound_without_H3K4me3,percent_svbf7_unbound_without_H3K4me3)

H3K4me3_present = c(percent_svbf7_H3K4me3_bound,percent_svbf7_H3K4me3_unbound)

data_H3K4me3 = data.frame(etat_svb,H3K4me3_absent,H3K4me3_present)
datatable(data_H3K4me3,rownames = F,filter = "none",colnames = c("Regions without H3K4me3","Regions with H3K4me3" ))
fig4 = plot_ly(data_H3K4me3, x = ~etat_svb,y = ~H3K4me3_absent, type = "bar",name = "H3K4me3 absent")
fig4 = fig4 %>% add_trace(y = ~H3K4me3_present, name = "H3K4me3 present")
fig4 = fig4 %>% layout(yaxis = list(title = "percent"))
fig4 = fig4 %>% layout(title = "H3K4me3 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig4

2.2 Comparaison avec les histones pour les motifs fixés ou non avec les pics S2 uniquement

2.2.1 H3K27ac

in H3K27ac absent H3K27ac
in svbF7 unbound 193 745
absent svbF7 unbound 4955 7979
in H3K27ac absent H3K27ac
in svbF7 bound 169 24
absent svbF7 bound 4981 8782
pvalue_fixe = phyper(169 - 1, 193, 13956 - 193, 5150)
pvalue_nonfixe = phyper(193 - 1, 938, 13872 - 938, 5148)


presence = c(169,4981)
absence = c(24,8782)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K27ac_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K27ac_fixe)

presence = c(193,4955)
absence = c(745,7979)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K27ac_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K27ac_nonfixe)

La pvalue du test de hypergéométrique pour les motifs fixé est de 1 Celle du test de hypergéométrique pour les motifs non fixé est de 3.611226810^{-30}

La pvalue du test de fisher pour les motifs fixé est de 6.843549410^{-49} Celle du test de fisher pour les motifs non fixé est de 1.590738210^{-29}`

total_svbF7_unbound_H3K27ac = 193 + 745
total_svbF7_bound_H3K27ac = 169 + 24

percent_svbf7_H3K27ac_unbound = round(100 * 193 / total_svbF7_unbound_H3K27ac, 2 ) 
percent_svbf7_unbound_without_H3K27ac = round(100 * 745 / total_svbF7_unbound_H3K27ac, 2 ) 

percent_svbf7_H3K27ac_bound = round(100 * 169 / total_svbF7_bound_H3K27ac, 2 ) 
percent_svbf7_bound_without_H3K27ac = round(100 * 24 / total_svbF7_bound_H3K27ac, 2 ) 


etat_svb = c("svbF7_bound","svb_unbound")
H3K27ac_absent = c(percent_svbf7_bound_without_H3K27ac,percent_svbf7_unbound_without_H3K27ac)

H3K27ac_present = c(percent_svbf7_H3K27ac_bound,percent_svbf7_H3K27ac_unbound)

data_H3K27ac = data.frame(etat_svb,H3K27ac_absent,H3K27ac_present)
datatable(data_H3K27ac,rownames = F,filter = "none",colnames = c("Regions without H3K27ac","Regions with H3K27ac" ))
fig1 = plot_ly(data_H3K27ac, x = ~etat_svb,y = ~H3K27ac_absent, type = "bar",name = "H3K27ac absent")
fig1 = fig1 %>% add_trace(y = ~H3K27ac_present, name = "H3K27ac present")
fig1 = fig1 %>% layout(yaxis = list(title = "percent"))
fig1 = fig1 %>% layout(title = "H3K27ac enrichment on svbF7 bound or not by Svb")
fig1
fig1 = plot_ly(data_H3K27ac, x = ~etat_svb,y = ~H3K27ac_absent, type = "bar",name = "H3K27ac absent")
fig1 = fig1 %>% add_trace(y = ~H3K27ac_present, name = "H3K27ac present")
fig1 = fig1 %>% layout(yaxis = list(title = "percent"))
fig1 = fig1 %>% layout(title = "H3K27ac enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig1

2.2.2 H3K27me3

in H3K27me3 absent H3K27me3
in svbF7 unbound 1241 0
absent svbF7 unbound 12191 4566
in H3K27me3 absent H3K27me3
in svbF7 bound 125 68
absent svbF7 bound 13313 4633
pvalue_fixe = phyper(125 - 1, 193, 18139 - 193, 13438)
pvalue_nonfixe = phyper(1241 - 1, 938, 17998 - 938, 13432)



presence = c(125,13313)
absence = c(68,4633)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K27me3_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K27me3_fixe)

presence = c(1241,12191)
absence = c(0,4566)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K27me3_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K27me3_nonfixe)

La pvalue du test de hypergéométrique pour les motifs fixé est de 0.0015224 Celle du test de hypergéométrique pour les motifs non fixé est de 1

La pvalue du test de fisher pour les motifs fixé est de 0.0037899 Celle du test de fisher pour les motifs non fixé est de 8.667719310^{-165}`

total_svbF7_unbound_H3K27me3 = 1241 + 0
total_svbF7_bound_H3K27me3 = 125 + 68

percent_svbf7_H3K27me3_unbound = round(100 * 1241 / total_svbF7_unbound_H3K27me3, 2 ) 
percent_svbf7_unbound_without_H3K27me3 = round(100 * 0 / total_svbF7_unbound_H3K27me3, 2 ) 

percent_svbf7_H3K27me3_bound = round(100 * 125 / total_svbF7_bound_H3K27me3, 2 ) 
percent_svbf7_bound_without_H3K27me3 = round(100 * 68 / total_svbF7_bound_H3K27me3, 2 ) 


etat_svb = c("svbF7_bound","svbF7_unbound")
H3K27me3_absent = c(percent_svbf7_bound_without_H3K27me3,percent_svbf7_unbound_without_H3K27me3)

H3K27me3_present = c(percent_svbf7_H3K27me3_bound,percent_svbf7_H3K27me3_unbound)

data_H3K27me3 = data.frame(etat_svb,H3K27me3_absent,H3K27me3_present)
datatable(data_H3K27me3,rownames = F,filter = "none",colnames = c("Regions without H3K27me3","Regions with H3K27me3" ))
fig2 = plot_ly(data_H3K27me3, x = ~etat_svb,y = ~H3K27me3_absent, type = "bar",name = "H3K27me3 absent")
fig2 = fig2 %>% add_trace(y = ~H3K27me3_present, name = "H3K27me3 present")
fig2 = fig2 %>% layout(yaxis = list(title = "percent"))
fig2 = fig2 %>% layout(title = "H3K27me3 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig2

2.2.3 H3K4me1

in H3K4me1 absent H3K4me1
in svbF7 unbound 324 614
absent svbF7 unbound 8441 6309
in H3K4me1 absent H3K4me1
in svbF7 bound 246 0
absent svbF7 bound 8522 7027
pvalue_fixe = phyper(246 - 1, 193, 15795 - 193, 8768)
pvalue_nonfixe = phyper(324 - 1, 938, 15688 - 938, 8765)


presence = c(246,8522)
absence = c(0,7027)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K4me1_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K4me1_fixe)

presence = c(324,8441)
absence = c(614,6309)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K4me1_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K4me1_nonfixe)

La pvalue du test de hypergéométrique pour les motifs fixé est de 1 Celle du test de hypergéométrique pour les motifs non fixé est de 2.462952910^{-42}

La pvalue du test de fisher pour les motifs fixé est de 5.06375710^{-64} Celle du test de fisher pour les motifs non fixé est de 1.095848110^{-41}`

total_svbF7_unbound = 324 + 614
total_svbF7_bound = 246 + 0 

percent_svbf7_H3K4me1_unbound = round(100 * 324 / total_svbF7_unbound, 2 ) 
percent_svbf7_unbound_without_H3K4me1 = round(100 * 614 / total_svbF7_unbound, 2 ) 

percent_svbf7_H3K4me1_bound = round(100 * 246 / total_svbF7_bound, 2 ) 
percent_svbf7_bound_without_H3K4me1 = round(100 * 0 / total_svbF7_bound, 2 ) 



etat_svb = c("svbF7_bound","svbF7_unbound")
H3K4me1_absent = c(percent_svbf7_bound_without_H3K4me1,percent_svbf7_unbound_without_H3K4me1)

H3K4me1_present = c(percent_svbf7_H3K4me1_bound,percent_svbf7_H3K4me1_unbound)

data_H3K4me1 = data.frame(etat_svb,H3K4me1_absent,H3K4me1_present)
datatable(data_H3K4me1,rownames = F,filter = "none", colnames = c("Regions without H3K4me1","Regions with H3K4me1" ))
fig3 = plot_ly(data_H3K4me1, x = ~etat_svb,y = ~H3K4me1_absent, type = "bar",name = "H3K4me1 absent")
fig3 = fig3 %>% add_trace(y = ~H3K4me1_present, name = "H3K4me1 present")
fig3 = fig3 %>% layout(yaxis = list(title = "percent"))
fig3 = fig3 %>% layout(title = "H3K4me1 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig3

2.2.4 H3K4me3

in H3K4me3 absent H3K4me3
in svbF7 unbound 92 846
absent svbF7 unbound 4715 11329
in H3K4me3 absent H3K4me3
in svbF7 bound 139 54
absent svbF7 bound 4668 12246
pvalue_fixe = phyper(139 - 1, 193, 17107 - 193, 4807)
pvalue_nonfixe = phyper(92 - 1, 938, 16982 - 938, 4807)

presence = c(139,4668)
absence = c(54,12246)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K4me3_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K4me3_fixe)

presence = c(92,4715)
absence = c(846,11329)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K4me3_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K4me3_nonfixe)

La pvalue du test de hypergéométrique pour les motifs fixé est de 1 Celle du test de hypergéométrique pour les motifs non fixé est de 1.633496410^{-46}

La pvalue du test de fisher pour les motifs fixé est de 5.465460810^{-37} Celle du test de fisher pour les motifs non fixé est de 1.080796610^{-45}`

total_svbF7_unbound_H3K4me3 = 92 + 846
total_svbF7_bound_H3K4me3 = 139 + 54

percent_svbf7_H3K4me3_unbound = round(100 * 92 / total_svbF7_unbound_H3K4me3, 2 ) 
percent_svbf7_unbound_without_H3K4me3 = round(100 * 846 / total_svbF7_unbound_H3K4me3, 2 ) 

percent_svbf7_H3K4me3_bound = round(100 * 139 / total_svbF7_bound_H3K4me3, 2 ) 
percent_svbf7_bound_without_H3K4me3 = round(100 * 54 / total_svbF7_bound_H3K4me3, 2 ) 



etat_svb = c("svbF7_bound","svbF7_unbound")
H3K4me3_absent = c(percent_svbf7_bound_without_H3K4me3,percent_svbf7_unbound_without_H3K4me3)

H3K4me3_present = c(percent_svbf7_H3K4me3_bound,percent_svbf7_H3K4me3_unbound)

data_H3K4me3 = data.frame(etat_svb,H3K4me3_absent,H3K4me3_present)
datatable(data_H3K4me3,rownames = F,filter = "none",colnames = c("Regions without H3K4me3","Regions with H3K4me3" ))
fig4 = plot_ly(data_H3K4me3, x = ~etat_svb,y = ~H3K4me3_absent, type = "bar",name = "H3K4me3 absent")
fig4 = fig4 %>% add_trace(y = ~H3K4me3_present, name = "H3K4me3 present")
fig4 = fig4 %>% layout(yaxis = list(title = "percent"))
fig4 = fig4 %>% layout(title = "H3K4me3 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig4

2.3 Comparaison avec les histones pour les motifs fixés ou non avec les pics dans les embryons

2.3.1 H3K27ac

in H3K27ac absent H3K27ac
in svbF7 unbound 193 745
absent svbF7 unbound 4955 7979
in H3K27ac absent H3K27ac
in svbF7 bound 98 401
absent svbF7 bound 5050 8036
pvalue_fixe = phyper(98 - 1, 499, 13585 - 499, 5148)
pvalue_nonfixe = phyper(193 - 1, 938, 13872 - 938, 5148)

presence = c(98,5050)
absence = c(401,8036)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K27ac_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K27ac_fixe)

presence = c(193,4955)
absence = c(745,7979)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K27ac_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K27ac_nonfixe)

La pvalue du test de hypergéométrique pour les motifs fixé est de 9.28454310^{-20} Celle du test de hypergéométrique pour les motifs non fixé est de 3.611226810^{-30}

La pvalue du test de fisher pour les motifs fixé est de 3.637514510^{-19} Celle du test de fisher pour les motifs non fixé est de 1.590738210^{-29}`

total_svbF7_unbound_H3K27ac = 193 + 745
total_svbF7_bound_H3K27ac = 98 + 401

percent_svbf7_H3K27ac_unbound = round(100 * 193 / total_svbF7_unbound_H3K27ac, 2 ) 
percent_svbf7_unbound_without_H3K27ac = round(100 * 745 / total_svbF7_unbound_H3K27ac, 2 ) 

percent_svbf7_H3K27ac_bound = round(100 * 98 / total_svbF7_bound_H3K27ac, 2 ) 
percent_svbf7_bound_without_H3K27ac = round(100 * 401 / total_svbF7_bound_H3K27ac, 2 ) 


etat_svb = c("svbF7_bound","svb_unbound")
H3K27ac_absent = c(percent_svbf7_bound_without_H3K27ac,percent_svbf7_unbound_without_H3K27ac)

H3K27ac_present = c(percent_svbf7_H3K27ac_bound,percent_svbf7_H3K27ac_unbound)

data_H3K27ac = data.frame(etat_svb,H3K27ac_absent,H3K27ac_present)
datatable(data_H3K27ac,rownames = F,filter = "none",colnames = c("Regions without H3K27ac","Regions with H3K27ac" ))
fig1 = plot_ly(data_H3K27ac, x = ~etat_svb,y = ~H3K27ac_absent, type = "bar",name = "H3K27ac absent")
fig1 = fig1 %>% add_trace(y = ~H3K27ac_present, name = "H3K27ac present")
fig1 = fig1 %>% layout(yaxis = list(title = "percent"))
fig1 = fig1 %>% layout(title = "H3K27ac enrichment on svbF7 bound or not by Svb")
fig1
fig1 = plot_ly(data_H3K27ac, x = ~etat_svb,y = ~H3K27ac_absent, type = "bar",name = "H3K27ac absent")
fig1 = fig1 %>% add_trace(y = ~H3K27ac_present, name = "H3K27ac present")
fig1 = fig1 %>% layout(yaxis = list(title = "percent"))
fig1 = fig1 %>% layout(title = "H3K27ac enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig1

2.3.2 H3K27me3

in H3K27me3 absent H3K27me3
in svbF7 unbound 1241 0
absent svbF7 unbound 12191 4566
in H3K27me3 absent H3K27ac
in svbF7 bound 672 0
absent svbF7 bound 12763 4083
pvalue_fixe = phyper(672 - 1, 499, 17518 - 499, 13435)
pvalue_nonfixe = phyper(1241 - 1, 938, 17998 - 938, 13432)


presence = c(672,12763)
absence = c(0,4083)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K27me3_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K27me3_fixe)

presence = c(1241,12191)
absence = c(0,4566)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K27me3_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K27me3_nonfixe)

La pvalue du test de hypergéométrique pour les motifs fixé est de 1 Celle du test de hypergéométrique pour les motifs non fixé est de 1

La pvalue du test de fisher pour les motifs fixé est de 1.19376610^{-79} Celle du test de fisher pour les motifs non fixé est de 8.667719310^{-165}`

total_svbF7_unbound_H3K27me3 = 1241 + 0
total_svbF7_bound_H3K27me3 = 672 + 0

percent_svbf7_H3K27me3_unbound = round(100 * 1241 / total_svbF7_unbound_H3K27me3, 2 ) 
percent_svbf7_unbound_without_H3K27me3 = round(100 * 0 / total_svbF7_unbound_H3K27me3, 2 ) 

percent_svbf7_H3K27me3_bound = round(100 * 672 / total_svbF7_bound_H3K27me3, 2 ) 
percent_svbf7_bound_without_H3K27me3 = round(100 * 0 / total_svbF7_bound_H3K27me3, 2 ) 


etat_svb = c("svbF7_bound","svbF7_unbound")
H3K27me3_absent = c(percent_svbf7_bound_without_H3K27me3,percent_svbf7_unbound_without_H3K27me3)

H3K27me3_present = c(percent_svbf7_H3K27me3_bound,percent_svbf7_H3K27me3_unbound)

data_H3K27me3 = data.frame(etat_svb,H3K27me3_absent,H3K27me3_present)
datatable(data_H3K27me3,rownames = F,filter = "none",colnames = c("Regions without H3K27me3","Regions with H3K27me3" ))
fig2 = plot_ly(data_H3K27me3, x = ~etat_svb,y = ~H3K27me3_absent, type = "bar",name = "H3K27me3 absent")
fig2 = fig2 %>% add_trace(y = ~H3K27me3_present, name = "H3K27me3 present")
fig2 = fig2 %>% layout(yaxis = list(title = "percent"))
fig2 = fig2 %>% layout(title = "H3K27me3 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig2

2.3.3 H3K4me1

in H3K4me1 absent H3K4me1
in svbF7 unbound 324 614
absent svbF7 unbound 8441 6309
in H3K4me1 absent H3K4me1
in svbF7 bound 259 240
absent svbF7 bound 8507 6316
pvalue_fixe = phyper(259 - 1, 499, 15322 - 499, 8766)
pvalue_nonfixe = phyper(324 - 1, 938, 15688 - 938, 8765)



presence = c(259,8507)
absence = c(240,6316)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K4me1_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K4me1_fixe)

presence = c(324,8441)
absence = c(614,6309)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K4me1_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K4me1_nonfixe)

La pvalue du test de hypergéométrique pour les motifs fixé est de 0.0066816 Celle du test de hypergéométrique pour les motifs non fixé est de 2.462952910^{-42}

La pvalue du test de fisher pour les motifs fixé est de 0.016689 Celle du test de fisher pour les motifs non fixé est de 1.095848110^{-41}`

total_svbF7_unbound = 324 + 614
total_svbF7_bound = 246 + 0 

percent_svbf7_H3K4me1_unbound = round(100 * 324 / total_svbF7_unbound, 2 ) 
percent_svbf7_unbound_without_H3K4me1 = round(100 * 614 / total_svbF7_unbound, 2 ) 

percent_svbf7_H3K4me1_bound = round(100 * 246 / total_svbF7_bound, 2 ) 
percent_svbf7_bound_without_H3K4me1 = round(100 * 0 / total_svbF7_bound, 2 ) 



etat_svb = c("svbF7_bound","svbF7_unbound")
H3K4me1_absent = c(percent_svbf7_bound_without_H3K4me1,percent_svbf7_unbound_without_H3K4me1)

H3K4me1_present = c(percent_svbf7_H3K4me1_bound,percent_svbf7_H3K4me1_unbound)

data_H3K4me1 = data.frame(etat_svb,H3K4me1_absent,H3K4me1_present)
datatable(data_H3K4me1,rownames = F,filter = "none", colnames = c("Regions without H3K4me1","Regions with H3K4me1" ))
fig3 = plot_ly(data_H3K4me1, x = ~etat_svb,y = ~H3K4me1_absent, type = "bar",name = "H3K4me1 absent")
fig3 = fig3 %>% add_trace(y = ~H3K4me1_present, name = "H3K4me1 present")
fig3 = fig3 %>% layout(yaxis = list(title = "percent"))
fig3 = fig3 %>% layout(title = "H3K4me1 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig3

2.3.4 H3K4me3

in H3K4me3 absent H3K4me3
in svbF7 unbound 92 846
absent svbF7 unbound 4715 11329
in H3K4me3 absent H3K4me3
in svbF7 bound 58 441
absent svbF7 bound 4749 11305
pvalue_fixe = phyper(58 - 1, 499, 16553 - 499, 4807)
pvalue_nonfixe = phyper(92 - 1, 938, 16982 - 938, 4807)

presence = c(58,4749)
absence = c(441,11305)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K4me3_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K4me3_fixe)

presence = c(92,4717)
absence = c(849,11329)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K4me3_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K4me3_nonfixe)

La pvalue du test de hypergéométrique pour les motifs fixé est de 8.590137410^{-22} Celle du test de hypergéométrique pour les motifs non fixé est de 1.633496410^{-46}

La pvalue du test de fisher pour les motifs fixé est de 4.7061110^{-21} Celle du test de fisher pour les motifs non fixé est de 4.936237910^{-46}`

total_svbF7_unbound_H3K4me3 = 92 + 846
total_svbF7_bound_H3K4me3 = 58 + 441

percent_svbf7_H3K4me3_unbound = round(100 * 92 / total_svbF7_unbound_H3K4me3, 2 ) 
percent_svbf7_unbound_without_H3K4me3 = round(100 * 846 / total_svbF7_unbound_H3K4me3, 2 ) 

percent_svbf7_H3K4me3_bound = round(100 * 58 / total_svbF7_bound_H3K4me3, 2 ) 
percent_svbf7_bound_without_H3K4me3 = round(100 * 441 / total_svbF7_bound_H3K4me3, 2 ) 



etat_svb = c("svbF7_bound","svbF7_unbound")
H3K4me3_absent = c(percent_svbf7_bound_without_H3K4me3,percent_svbf7_unbound_without_H3K4me3)

H3K4me3_present = c(percent_svbf7_H3K4me3_bound,percent_svbf7_H3K4me3_unbound)

data_H3K4me3 = data.frame(etat_svb,H3K4me3_absent,H3K4me3_present)
datatable(data_H3K4me3,rownames = F,filter = "none",colnames = c("Regions without H3K4me3","Regions with H3K4me3" ))
fig4 = plot_ly(data_H3K4me3, x = ~etat_svb,y = ~H3K4me3_absent, type = "bar",name = "H3K4me3 absent")
fig4 = fig4 %>% add_trace(y = ~H3K4me3_present, name = "H3K4me3 present")
fig4 = fig4 %>% layout(yaxis = list(title = "percent"))
fig4 = fig4 %>% layout(title = "H3K4me3 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig4

3 Conclusion

Nous observons que les motifs svbF7 communs fixés entre les S2 et les embryons montrent un enrichissement en H3K4me1, H3K4me3 et H3K27ac. Cet enrichissement est également visible pour les motifs svbF7 fixé uniquement dans les embryons. Les motifs svbf7 des embryons sont enrichi en H3K27me3 et H3K4me1.